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1 STOCKHOLM UNIVERSITY Department of Economics Course name: Empirical methods 2 Course code: EC2402 Examiner: Per Pettersson-Lidbom Number of credits: 7,5 credits Date of exam: Sunday 21 February 2010 Examination time: 3 hours Write your identification number on each paper and cover sheet (the number stated in the upper right hand corner on your exam cover). Do not write answers to more than one question in the same cover sheet. Explain notions/concepts and symbols. If you think that a question is vaguely formulated, specify the conditions used for solving it. Only legible exams will be marked. No aids are allowed The exam consists of two parts. Part 1 consists of 20 multiple choice questions worth 40 points in total (2 points each). All students must answer this part of the exam. Part 2 consists of two discussion questions worth 60 points in total (30 points each). If you have received credit you do not need to answer discussion question 1. The exam is worth 100 points in total. For the grade E 40 points are required, for D 50 points, C 60 points, B 75 points and A 90 points Results will be posted on the notice board, House A, floor 3, on March the latest Good luck!

2 Part 1: Multiple Choice Questions (40 points) Circle the right answer. Only one answer per question. No credit will be given for multiple answers or additional explanations. Two points per question for correct answers. 1. In the case of errors-in-variables bias, a. maximum likelihood estimation must be used. b. the OLS estimator is consistent if the variance in the unobservable variable is relatively large compared to variance in the measurement error. c. the OLS estimator is consistent, but no longer unbiased in small samples. d. binary variables should not be used as independent variables. 2. Sample selection bias occurs when a. the choice between two samples is made by the researcher. b. data are collected from a population by simple random sampling. c. samples are chosen to be small rather than large. d. the availability of the data is influenced by a selection process that is related to the value of the dependent variable. 3. Simultaneous causality a. means you must run a second regression of X on Y. b. leads to correlation between the regressor and the error term. c. means that a third variable affects both Y and X. d. cannot be established since regression analysis only detects correlation between variables. 4. Correlation of the regression error across observations a. results in incorrect OLS standard errors. b. makes the OLS estimator inconsistent, but not unbiased. c. results in correct OLS standard errors if heteroskedasticity-robust standard errors are used. d. is not a problem in cross-sections since the data can always be reshuffled.

3 5. Applying the analysis from the California test scores to another U.S. state is an example of looking for a. simultaneous causality bias. b. external validity. c. sample selection bias. d. internal validity. 6. In the Fixed Time Effects regression model, you should exclude one of the binary variables for the time periods when an intercept is present in the equation a. because the first time period must always excluded from your data set. b. because there are already too many coefficients to estimate. c. to avoid perfect multicollinearity. d. to allow for some changes between time periods to take place. 7. If you included both time and entity fixed effects in the regression model which includes a constant, then a. one of the explanatory variables needs to be excluded to avoid perfect multicollinearity. b. you can use the before and after specification even for T > 2. c. you must exclude one of the entity binary variables and one of the time binary variables for the OLS estimator to exist. d. the OLS estimator no longer exists. 8. Consider the regression example from your textbook, which estimates the effect of beer taxes on fatality rates across the 48 contiguous U.S. states. If beer taxes were set nationally by the federal government rather than by the states, then a. it would not make sense to use state fixed effect. b. you can test state fixed effects using homoskedastic-only standard errors. c. the OLS estimator will be biased. d. you should not use time fixed effects since beer taxes are the same at a point in time across states. 9. In the linear probability model, the interpretation of the slope coefficient is a. the change in odds associated with a unit change in X, holding other regressors constant. b. not all that meaningful since the dependent variable is either 0 or 1. c. the change in probability that Y=1 associated with a unit change in X, holding others regressors constant. d. the response in the dependent variable to a percentage change in the regressor.

4 10. The major flaw of the linear probability model is that a. the actuals can only be 0 and 1, but the predicted are almost always different from that. b. the regression R 2 cannot be used as a measure of fit. c. people do not always make clear-cut decisions. d. the predicted values can lie above 1 and below The distinction between endogenous and exogenous variables is a. that exogenous variables are determined inside the model and endogenous variables are determined outside the model. b. dependent on the sample size: for n > 100, endogenous variables become exogenous. c. depends on the distribution of the variables: when they are normally distributed, they are exogenous, otherwise they are endogenous. d. whether or not the variables are correlated with the error term. 12. Instrument relevance a. means that the instrument is one of the determinants of the dependent variable. b. is the same as instrument exogeneity. c. means that some of the variance in the regressor is related to variation in the instrument. d. is not possible since X and u are correlated and Z and u are not correlated. 13. Consider a competitive market where the demand and the supply depend on the current price of the good. Then fitting a line through the quantity-price outcomes will a. give you an estimate of the demand curve. b. estimate neither a demand curve nor a supply curve. c. enable you to calculate the price elasticity of supply. d. give you the exogenous part of the demand in the first stage of TSLS. 14. The TSLS estimator is a. consistent and has a normal distribution in large samples. b. unbiased. c. efficient in small samples. d. F-distributed.

5 15. The reduced form equation for X a. regresses the endogenous variable X on the smallest possible subset of regressors. b. relates the endogenous variable X to all the available exogenous variables, both those included in the regression of interest and the instruments. c. uses the predicted values of X from the first stage as a regressor in the original equation. d. uses smaller standard errors, such as homoskedasticity-only standard errors, for inference. 16. Having more relevant instruments a. is a problem because instead of being just identified, the regression now becomes overidentified. b. is like having a larger sample size in that the more information is available for use in the IV regressions. c. typically results in larger standard errors for the TSLS estimator. d. is not as important for inference as having the same number of endogenous variables as instruments. 17. Experimental data are often a. observational data. b. binary data, in that the subject either does or does not respond to the treatment. c. panel data. d. time series data. 18. With panel data, the causal effect a. cannot be estimated since correlation does not imply causation. b. is typically estimated using the probit regression model. c. can be estimated using the differences-in-differences estimator. d. can be estimated by looking at the difference between the treatment and the control group after the treatment has taken place. 19. Causal effects that depend on the value of an observable variable, say W i, a. cannot be estimated. b. can be estimate by interacting the treatment variable with W i. c. result in the OLS estimator being inefficient. d. requires use of homoskedasticity-only standard errors.

6 20. In a quasi-experiment a. quasi differences are used, i.e., instead of Y you need to use after before ( Y Y ), where 0 1. b. randomness is introduced by variations in individual circumstances that make it appear as if the treatment is randomly assigned. c. the causal effect has to be estimated through quasi maximum likelihood estimation. d. the t-statistic is no longer normally distributed in large samples.

7 Part 2: Discussion Questions (60 points) On separate sheets of paper, answer the following two discussion questions. Write your name, personal number (personnummer) and the question number on each sheet. Answer each question clearly and concisely. Only legible answers will be considered, others will be disregarded. If you think that a question is vaguely formulated, specify the conditions used for solving it. Each question is worth 30 points. Discussion question 1: NOTE: Those with a credit receive 30 points for this question and do not have to answer discussion question 1. Using two of the examples from your textbook, describe econometric studies which required instrumental variable techniques. In each case emphasize why the need for instrumental variables arises and how authors have approached the problem. Make sure to include a discussion of overidentification, the validity of instruments, and testing procedures in your essay. Discussion question 2: Canada and the United States had approximately the same aggregate unemployment rates from the 1920s to In 1982, a two percentage point gap appears, which has roughly persisted until today, with the Canadian unemployment rate in the third quarter of 2002 being 7.6 percent while the American rate stood at 5.9 percent in the same period. Several authors have investigated this phenomenon. One study, published in 1990, contained the following statement: It is a clichė that, as compared to analysis in the physical sciences, economic analysis is hampered by the lack of controlled experiments. In this regard, study of the Canadian economy can be much facilitated by comparison with the behaviour of the US Discuss what the authors may have had in mind. List some potential threats to internal and external validity when comparing aggregate unemployment rate behavior between countries.

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